<i>Qanuq ukua kanguit sunialiqpitigu?</i> (What should we do with all of these geese?) Collaborative research to support wildlife co-management and Inuit self-determination
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Inuit living in Nunavut have harvested light geese and lived near goose colonies for generations. Inuit knowledge includes important information about light goose ecology and management that can inform co-management and enhance scientific research and monitoring. Since the 1970s, populations of light geese (Snow and Ross’ Geese; kanguit and kangunnait in Inuktut; Chen caerulescens (Linnaeus, 1758) and Chen rossii (Cassin, 1861)) have experienced significant increases in abundance which led to habitat alteration in some portions of the central and eastern Canadian Arctic. In response to concerns expressed by Inuit and wildlife managers about light goose abundance, we conducted a collaborative research project in Arviat and Salliq (Coral Harbour), Nunavut, aiming to mobilize and document Inuit knowledge about light goose ecology and management in the Kivalliq region. Here, we explore the potential of collaborative research for mobilizing Inuit knowledge to support informed and inclusive decision-making about wildlife resources. First, we describe the participatory research methods employed to explore Inuit-identified management recommendations for light geese and engage co-management partners and research contributors to explore select management options. Then, we present these light goose management recommendations and options. Lastly, we discuss opportunities and challenges around the use of collaborative research to support wildlife co-management and Inuit self-determination. Inuit nunaqaqtut Nunavuumi angunasuksimalirmata kanguqpangnik kangurniglu nunaqarvingita sanianni araagunik unuqtunnik. Inuit qaujimaningat ilaqaqpuq aturnilingnik kanguit niqinginnik mianirijauninginniklu tusaumatitaulutik qaujisarningit mianiriyaunigillu. Taimangat 1970s atuqtilugit, kanguit unirningit (kanguit amma kanguaryuit Inuktut; Chen caerulescens (Linnaeus, 1758) amma Chen rossii (Cassin, 1861)) ayunganaqtukut pisimangmata unulialiqlutik amma niqiqatiarungnauqlutik Kanataup uqiuktaqtunngani. Tamana piblugu Inuit uumayuliriyillu isumaalulirmata kanguit unulualirninginnik, taima qaujisarnirmik pigialauqpugut Arvianni and Sallim (Coral Harbour), Nunavuumi, aulataulutik amma qaujisagaulutik Inuit kaujimajagit kangurnik Kivallirmi. Tavani atuqtuuluaqtunik qaujisarnirmut mianiqsinirmullu pitaqaqpuq Inuit nagminiq isumaliurlutik nirjutinut atugaksanullu. Sivullirmik, qaujisarniup qanuinninga isumagilugu kanguit mianirijauninginut. Amma suli, uqausirilirlugu kanguit mianirijauningat atugaujuuluaqtullu. Kingulirmik, uqausirilugu atuinnaujut amma ajurutaujut qaujisarniup iluanni nirjutinik amma Inuit nagminiq aulatuulualirninginnik.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it